Search engines are often assessed based on two metrics: recall and precision. Recall is the ratio between the number of relevant results returned and the total number that exist in the collection being searched. Precision is the ratio between the number of relevant results returned and the size of the result set returned by the search. Typically, search engines rely on large-scale indexes which include an entire collection of data and are very time consuming to create and maintain. Moreover, optimizing such search engines to perform well in one respect (e.g. to return relevant results to boost precision) can easily impact the other (e.g. fewer results are returned, including relevant ones, thus lowering recall).